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  • Open Access

    ARTICLE

    Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

    Umer Nauman1, Yuhong Zhang2, Zhihui Li3, Tong Zhen1,3,*

    Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 15-34, 2024, DOI:10.32604/jimh.2024.048784

    Abstract The convergence of handheld devices and cloud-based computing has transformed how Electronic Health Records (EHRs) are stored in mobile cloud paradigms, offering benefits such as affordability, adaptability, and portability. However, it also introduces challenges regarding network security and data confidentiality, as it aims to exchange EHRs among mobile users while maintaining high levels of security. This study proposes an innovative blockchain-based solution to these issues and presents secure cloud storage for healthcare data. To provide enhanced cryptography, the proposed method combines an enhanced Blowfish encryption method with a new key generation technique called Elephant Herding Optimization with Resistance-Based Training (EHO-RBT).… More >

  • Open Access

    ARTICLE

    Inhibition of Ehrlich ascites carcinoma growth by melatonin: Studies with micro-CT

    SEHER YILMAZ1,2,*, ZÜLEYHA DOĞANYIĞIT3, MERT OCAK4, EVRIM SUNA ARIKAN SÖYLEMEZ5, ASLI OKAN OFLAMAZ3, SÜMEYYE UÇAR6, ŞÜKRÜ ATEŞ1, AMMAD AHMAD FAROOQI7

    Oncology Research, Vol.32, No.1, pp. 175-185, 2024, DOI:10.32604/or.2023.042350

    Abstract Melatonin is a versatile indolamine synthesized and secreted by the pineal gland in response to the photoperiodic information received by the retinohypothalamic signaling pathway. Melatonin has many benefits, such as organizing circadian rhythms and acting as a powerful hormone. We aimed to show the antitumor effects of melatonin in both in vivo and in vitro models through the mammalian target of rapamycin (mTOR) signaling pathway and the Argyrophilic Nucleolar Regulatory Region (AgNOR), using the Microcomputed Tomography (Micro CT). Ehrlich ascites carcinoma (EAC) cells were administered into the mice by subcutaneous injection. Animals with solid tumors were injected intraperitoneally with 50… More > Graphic Abstract

    Inhibition of Ehrlich ascites carcinoma growth by melatonin: Studies with micro-CT

  • Open Access

    ARTICLE

    An Immutable Framework for Smart Healthcare Using Blockchain Technology

    Faneela1, Muazzam A. Khan1, Suliman A. Alsuhibany2,*, Walid El-Shafai3,4, Mujeeb Ur Rehman5, Jawad Ahmad6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 165-179, 2023, DOI:10.32604/csse.2023.035066

    Abstract The advancements in sensing technologies, information processing, and communication schemes have revolutionized the healthcare sector. Electronic Healthcare Records (EHR) facilitate the patients, doctors, hospitals, and other stakeholders to maintain valuable data and medical records. The traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks. A single attempt of a successful Denial of Service (DoS) attack can compromise the complete healthcare system. This article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things (IoMT) to address the stated challenges. The proposed architecture is on the idea of a lightweight private blockchain-based network that… More >

  • Open Access

    ARTICLE

    An Efficient Ensemble Model for Various Scale Medical Data

    Heba A. Elzeheiry*, Sherief Barakat, Amira Rezk

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1283-1305, 2022, DOI:10.32604/cmc.2022.027345

    Abstract Electronic Health Records (EHRs) are the digital form of patients’ medical reports or records. EHRs facilitate advanced analytics and aid in better decision-making for clinical data. Medical data are very complicated and using one classification algorithm to reach good results is difficult. For this reason, we use a combination of classification techniques to reach an efficient and accurate classification model. This model combination is called the Ensemble model. We need to predict new medical data with a high accuracy value in a small processing time. We propose a new ensemble model MDRL which is efficient with different datasets. The MDRL… More >

  • Open Access

    ARTICLE

    Unidirectional Identity-Based Proxy Re-Signature with Key Insulation in EHR Sharing System

    Yanan Chen1,2,3,4, Ting Yao1,4,*, Haiping Ren2, Zehao Gan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1497-1513, 2022, DOI:10.32604/cmes.2022.019589

    Abstract The introduction of the electronic medical record (EHR) sharing system has made a great contribution to the management and sharing of healthcare data. Considering referral treatment for patients, the original signature needs to be converted into a re-signature that can be verified by the new organization. Proxy re-signature (PRS) can be applied to this scenario so that authenticity and nonrepudiation can still be insured for data. Unfortunately, the existing PRS schemes cannot realize forward and backward security. Therefore, this paper proposes the first PRS scheme that can provide key-insulated property, which can guarantee both the forward and backward security of… More >

  • Open Access

    ARTICLE

    An Analysis of Integrating Machine Learning in Healthcare for Ensuring Confidentiality of the Electronic Records

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Alka Agrawal1, Nitish Pathak4, Rajeev Kumar5,6,*, Raees Ahmad Khan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1387-1422, 2022, DOI:10.32604/cmes.2022.018163

    Abstract The adoption of sustainable electronic healthcare infrastructure has revolutionized healthcare services and ensured that E-health technology caters efficiently and promptly to the needs of the stakeholders associated with healthcare. Despite the phenomenal advancement in the present healthcare services, the major obstacle that mars the success of E-health is the issue of ensuring the confidentiality and privacy of the patients’ data. A thorough scan of several research studies reveals that healthcare data continues to be the most sought after entity by cyber invaders. Various approaches and methods have been practiced by researchers to secure healthcare digital services. However, there are very… More >

  • Open Access

    ARTICLE

    A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

    Kirupa Shankar Komathi Maathavan1,*, Santhi Venkatraman2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 765-779, 2022, DOI:10.32604/iasc.2022.022276

    Abstract The major operation of the blood bank supply chain is to estimate the demand, perform inventory management and distribute adequate blood for the needs. The proliferation of big data in the blood bank supply chain and data management needs an intelligent, automated system to classify the essential data so that the requests can be handled easily with less human intervention. Big data in the blood bank domain refers to the collection, organization, and analysis of large volumes of data to obtain useful information. For this purpose, in this research work we have employed machine learning techniques to find a better… More >

  • Open Access

    ARTICLE

    Machine Learning Techniques Applied to Electronic Healthcare Records to Predict Cancer Patient Survivability

    Ornela Bardhi1,2,*, Begonya Garcia Zapirain1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326

    Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178 features for BCa and 143… More >

  • Open Access

    ARTICLE

    Blockchain-Enabled EHR Framework for Internet of Medical Things

    Lewis Nkenyereye1,*, S. M. Riazul Islam2, Mahmud Hossain3, M. Abdullah-Al-Wadud4, Atif Alamri4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 211-221, 2021, DOI:10.32604/cmc.2021.013796

    Abstract The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within… More >

  • Open Access

    ARTICLE

    A Fuzzy Ontological Infrastructure for Semantic Interoperability in Distributed Electronic Health Record

    Ebtsam Adel1, Shaker El-sappagh2, Mohammed Elmogy3, Sherif Barakat1, Kyung-Sup Kwak4,*

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 237-251, 2020, DOI:10.31209/2019.100000151

    Abstract Information technology is a beneficial tool for the healthcare industry. Health informatics is concerned with using ICT within the healthcare system. Different electronic health record (EHR) systems independently store large amounts of medical data in various structures and formats. Achieving semantic interoperability in EHR environments will improve the healthcare industry. In our previous studies, we proposed a framework that identifies the different heterogeneous medical data sources. In this paper, we move towards implementing the first module of that framework. We expect our framework to be a step towards improving performance and reducing both human mediation and data losses. More >

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